Prediction of lamb meat fatty acid composition using near-infrared reflectance spectroscopy (NIRS)

Guy, F.; Prache, Sophie; Thomas, Agnès; Bauchart, Dominique; Andueza, Donato

doi:10.1016/j.foodchem.2011.01.084

Cited by 93 publications

(47 citation statements)

References 24 publications

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“…to classify the geographical origins of lamb meats. Also good results were accounted by Guy et al (2011) that use the NIRS to predict lamb meat fatty acid composition. Calibrations from BÜCHI in Iberian pig meat for prediction chemical composition by Luna Delgado et al (2004) have produced results with the same accuracy for protein and moisture as the calibrations obtained this study.…”

Section: Resultsmentioning

confidence: 99%

An approach to predict chemical composition of goat Longissimus thoracis et lumborum muscle by Near Infrared Reflectance spectroscopy

Teixeira

Oliveira

Paulos

et al. 2015

Small Ruminant Research

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a b s t r a c tThe ability of near infrared reflectance spectroscopy (NIRS) to estimate the protein, moisture, connective tissue and ash content in the Longissimus thoracis et lumborum (LTL) muscle of goat was studied. Samples (n = 240) of the LTL muscle were taken from the 8th to 13th rib cut of goat carcasses. Samples were scanned in a FT-NIR Master TM N500 (BÜCHI) over a NIR spectral range of 4000-10,000 cm −1 with a resolution of 4 cm −1 . It was collected 3 spectra per sample and subsequently, chemical analyses were performed at the Carcass and Meat Quality Laboratory of ESA-IPB. Using NirCal 1.5 it was developed a PLS regression model assaying, first and second derivatives as math treatment and multiplicative scatter correction for minimizing scattering effect on the spectra database recorded (n = 240). The best calibrations' models show relatively good predictability for protein (standard error of prediction SEP = 0.43; coefficient of determination R 2 = 0.91), moisture (SEP = 0.48; R 2 = 0.92). Calibrations' models obtained are important as a first attempt to predict the chemical composition of goat meat by NIRS. More experimental data are needed to improve the accuracy of these calibrations.

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Section: Resultsmentioning

confidence: 99%

An approach to predict chemical composition of goat Longissimus thoracis et lumborum muscle by Near Infrared Reflectance spectroscopy

Teixeira

Oliveira

Paulos

et al. 2015

Small Ruminant Research

View full text Add to dashboard Cite

show abstract

“…More generally, to assess meat quality closer to the point of sale, different indicators (pH, color, mechanical properties, ultrasound, electrical impedance and conductivity, etc) and technologies (image analysis, fluorescence and NIR spectroscopy, etc) can be used (Meunier, Picard, Astruc & Labas, 2010;Dian, Andueza, Barbosa, Amoureux, Jestin, Carvalho, Prado et al, 2007;Guy, Prache, Thomas, Bauchart & Andueza, 2011). Final assessments by analytical tests with trained panels or consumer tests are methods that are chosen to evaluate meat sensory quality (reviewed by Hocquette et al, 2007b).…”

Section: Accepted M Manuscriptmentioning

confidence: 99%

Opportunities for predicting and manipulating beef quality

et al. 2012

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“…Equations for SFA and MUFA content (Table 3) (Sierra et al, 2008;Guy et al, 2011), and might be related to the narrow range PUFA, polyunsaturated fatty acids= C18:2n-6+C18:3n-3+C20:2n-6+C20:3n-6+C20:4n-6+C20:5n-3+C22:4n-6+C22:5n-3+C22:6n-3; 9 n-6= C18:2n-6+C20:2n-6+C20:3n-6+C20:4n-6+C22:4n-6; 10 n-3= C18:3n-3+C20:5n-3+C22:5n-3+C22:6n-3.…”

Section: Nirs Calibrationsmentioning

confidence: 99%

Application of NIRS for predicting fatty acids in intramuscular fat of rabbit

2012

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Accurate predictions were reported for IMF (R 2 CV=0.98; RPDCV=7.57), saturated (R 2 CV=0.96; RPDCV=5.08) and monounsaturated fatty acid content (R 2 CV=0.98; RPDCV=6.68). Lower accuracy was obtained for polyunsaturated fatty acid content (R 2 CV=0.83; RPDCV=2.40). Several individual fatty acids were accurately predicted such as C14:0, C15:0, C16:0, C16:1, C17:0, C18:0, C18:1 n-9, C18:2 n-6 and C18:3 n-3 (R 2 CV=0.91-0.97; RPDCV>3). Long chain polyunsaturated fatty acids and C18:1 n-7 presented less accurate prediction equations (R 2 CV=0.12-0.82; RPDCV<3).

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Prediction of lamb meat fatty acid composition using near-infrared reflectance spectroscopy (NIRS)

Cited by 93 publications

References 24 publications

An approach to predict chemical composition of goat Longissimus thoracis et lumborum muscle by Near Infrared Reflectance spectroscopy

An approach to predict chemical composition of goat Longissimus thoracis et lumborum muscle by Near Infrared Reflectance spectroscopy

Opportunities for predicting and manipulating beef quality

Application of NIRS for predicting fatty acids in intramuscular fat of rabbit

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